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2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery最新文献

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Representative Template Set Generation Method for Pedestrian Detection 行人检测代表性模板集生成方法
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.677
Pei Wu, Xianbin Cao, Yan Xu, Hong Qiao
{"title":"Representative Template Set Generation Method for Pedestrian Detection","authors":"Pei Wu, Xianbin Cao, Yan Xu, Hong Qiao","doi":"10.1109/FSKD.2008.677","DOIUrl":"https://doi.org/10.1109/FSKD.2008.677","url":null,"abstract":"Template matching is an effective approach for pedestrian detection. In order to achieve real-time and accurate detection, how to obtain a suitable representative template set is still an open problem due to the large variety of pedestrian shape. This paper introduced a representative template generation method for a template matching based pedestrian detection system (PDS). Based on nonlinear manifold learning and clustering, the new approach can generate a suitable representative template subset from a large amount of original templates. First, an improved nonlinear dimensionality reduction method was proposed to map original templates to feature vectors (points) in the low-dimensional embedding space; second, representative points were generated in the embedding space by clustering; at the end, corresponding representative template set were synthesized by mapping inversely the newly generated points from the embedding space to the visual input space.The experimental results showed that the template generation method speeds up detection procedure without considerable loss of performance.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127275361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Fuzzy Synthetic Evaluation of Water Quality with Membership Functions Constructed by Linear Interpolation 用线性插值构造隶属函数的水质模糊综合评价
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.207
Jun Yin, Zening Wu
{"title":"Fuzzy Synthetic Evaluation of Water Quality with Membership Functions Constructed by Linear Interpolation","authors":"Jun Yin, Zening Wu","doi":"10.1109/FSKD.2008.207","DOIUrl":"https://doi.org/10.1109/FSKD.2008.207","url":null,"abstract":"By analyzing traditional membership functions for fuzzy synthetic evaluation of water quality, some problems emerged: difficulties in determining parameters in traditional membership functions and insufficient samples for constructing proper membership functions. To solve these problems, more information was obtained by analyzing the shapes of traditional membership functions and the physical meaning of boundaries in water quality standard, and linear interpolation algorithm was applied to expand the sample size when considering the similar application for artificial neural network (ANN) evaluation of water quality. Finally, membership functions were constructed and a new method for evaluation water quality based on fuzzy synthetic evaluation was proposed. Comparisons between different evaluation methods show that the proposed method, grey relation analysis (GRA), and ANN are similar to each other, especially between GRA and the proposed method. These relations would be ascribed to fundamental assumptions of each method. For these similarities, the proposed method seems appropriate for evaluating water quality. The method may also provide some hints for other synthetic evaluation with similar problems concerning boundaries or inadequate sample size.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"1221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127435344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Optimal Model of Reservoir Flood Operation Considering Objective and Subjective Weight and Its Application 考虑主客观权重的水库防洪调度优化模型及其应用
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.414
Shufeng Xi, Jingxuan Yuan, Ji Liu
{"title":"Optimal Model of Reservoir Flood Operation Considering Objective and Subjective Weight and Its Application","authors":"Shufeng Xi, Jingxuan Yuan, Ji Liu","doi":"10.1109/FSKD.2008.414","DOIUrl":"https://doi.org/10.1109/FSKD.2008.414","url":null,"abstract":"According to the objective weigh provided by fuzzy iteration methodology, the paper presents the concept of weight tradeoff coefficient, combining subjective and objective weight together. Since the method takes into account, in the meantime, the objective intent of decision-maker and the natural property of alternative, the weight and relative member-ship degree are directly obtained from the recommended alternatives supplied by decision makers, the difficulty of weights determination can be avoided and the ranking of alternative is more feasible and reasonable.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125829420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on Real Estate Early Warning System Based on Decision Tree and Fuzzy Recognition Theory 基于决策树和模糊识别理论的房地产预警系统研究
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.24
Jianzhou Wang, Jinxing Che, Jinzhao Liang, H. Lu
{"title":"Research on Real Estate Early Warning System Based on Decision Tree and Fuzzy Recognition Theory","authors":"Jianzhou Wang, Jinxing Che, Jinzhao Liang, H. Lu","doi":"10.1109/FSKD.2008.24","DOIUrl":"https://doi.org/10.1109/FSKD.2008.24","url":null,"abstract":"This paper presents a pre-warning system developed to monitor and provide pre-warning to the governmental decision makers in real estate market, applying the grey relational analysis and model design method, with the fuzzy recognition theory based on decision tree and its effectiveness. The real estate early warning system has been designed successfully by the three sub-modules of feature selection on each non-terminating node, decision rule on each non-terminating node and a new fuzzy decision tree method, early warning for the real estate market. The article details analysis and recognition module, a set of factors are selected by grey relational analysis and fuzzy recognition early-warning method is used, which can monitor the real estate property market, is developed. Empirical results indicate that the pre-warning system can provide useful information to regulate the property market.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125933289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Disaster Assessment Algorithm after Forest Fire Based on GIS 基于GIS的森林火灾灾害评估算法
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.246
Aijun Xu, Minghui Ma
{"title":"Disaster Assessment Algorithm after Forest Fire Based on GIS","authors":"Aijun Xu, Minghui Ma","doi":"10.1109/FSKD.2008.246","DOIUrl":"https://doi.org/10.1109/FSKD.2008.246","url":null,"abstract":"This paper mainly focuses on the application of disaster assessment algorithm after forest fire and studies on the design and realization of disaster assessment based on GIS. After forest fire through the analysis and processing of multi-sources and heterogeneous data, this paper integrates the foundation that the domestic and foreign scholars laid of the research on assessment for forest fire loss with the related knowledge of assessment, accounting and forest resources appraisal so as to study and approach the theory framework and assessment index of the research on assessment for forest fire loss. The technologies of boundary extracted, overlay analysis, and division processing of multi-sources spatial data are available to realize the application of the investigation method of the burnt forest area and the computation of the fire area. The assessment provides evidence for fire cleaning in burnt areas and new policy making on restoration in terms of the direct and the indirect economic loss and ecological and environmental damage caused by forest fire under the condition of different fire danger classes and different amounts of forest accumulation, thus makes forest resources protection operated in a faster, more efficient and more economical way. Finally, this paper takes Linpsilaan city of Zhejiang province as a test area to confirm the method mentioned in the paper in terms of key technologies.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123428595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Application of Generalized Predictive Control to the HAGC 广义预测控制在HAGC中的应用
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.380
Xiaodong Zhang, Xiao-lan Yao, Qing-he Wu, Daoping Li
{"title":"The Application of Generalized Predictive Control to the HAGC","authors":"Xiaodong Zhang, Xiao-lan Yao, Qing-he Wu, Daoping Li","doi":"10.1109/FSKD.2008.380","DOIUrl":"https://doi.org/10.1109/FSKD.2008.380","url":null,"abstract":"Since generalized predictive control (GPC) has been introduced, it has been known as an effective tool for the control of many practical systems, but few literature about the application of generalized predictive control to the hydraulic automatic gauge control (HAGC) is concerned. Here, the generalized predictive control algorithm is employed to increases the thickness precision of strips, by decreasing the disadvantage effects of the roll eccentricity, and to improves the dynamic behavior of the hydraulic automatic gauge control. Simulation results demonstrate the feasibility and the excellent performance of the GPC algorithm.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125526781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Fuzzy Multi-objective Linear Programming Having Probabilistic Constraints: Application in Product-Mix Decision-Making 具有概率约束的模糊多目标线性规划在产品组合决策中的应用
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.681
I. Suharto, S. Susanto, Neneng Tintin Rosmiyanti, A. Bhattacharya
{"title":"Fuzzy Multi-objective Linear Programming Having Probabilistic Constraints: Application in Product-Mix Decision-Making","authors":"I. Suharto, S. Susanto, Neneng Tintin Rosmiyanti, A. Bhattacharya","doi":"10.1109/FSKD.2008.681","DOIUrl":"https://doi.org/10.1109/FSKD.2008.681","url":null,"abstract":"A fuzzy multi-objective linear programming model having probabilistic constraints is demonstrated in order to make product-mix decision. The proposed model considers fuzziness in presence of multiple objective functions. The most important aspect of the model is that it is able to tackle constraints which are probabilistic in nature. A product-mix problem having real-world data of a food processing industry is illustrated focusing the application of the proposed model.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114886967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
An Algorithm for Case-Based Reasoning Based on Similarity Rough Set 一种基于相似粗糙集的案例推理算法
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.13
S. Ji, Shenfang Yuan, Shui-ping Wang
{"title":"An Algorithm for Case-Based Reasoning Based on Similarity Rough Set","authors":"S. Ji, Shenfang Yuan, Shui-ping Wang","doi":"10.1109/FSKD.2008.13","DOIUrl":"https://doi.org/10.1109/FSKD.2008.13","url":null,"abstract":"A case selection algorithm selects representative cases from a large data set for future case-based reasoning tasks. This paper proposes the SRS algorithm, based on similarity-based rough set theory, which selects a reasonable number of the representative cases while maintaining satisfactory classification accuracy. It also can handle noise and inconsistent data. Experimental results have confirmed the algorithm feasibility and the validity.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114890367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A Feature Selection Algorithm Based on Boosting for Road Detection 一种基于Boosting的道路检测特征选择算法
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.550
Yun Sha, Xinhua Yu, Guoying Zhang
{"title":"A Feature Selection Algorithm Based on Boosting for Road Detection","authors":"Yun Sha, Xinhua Yu, Guoying Zhang","doi":"10.1109/FSKD.2008.550","DOIUrl":"https://doi.org/10.1109/FSKD.2008.550","url":null,"abstract":"Feature selection is very important for road detection. Generally, optimal feature set is very hard to be determined manually by prior-knowledge. In this paper, a feature selection algorithm based on boosting is proposed. To fully utilize potential feature correlations, the features are combined. The feature vector is enlarged by the combined features, and the new feature vector is called raw feature vector. In this paper, the classify power of each feature is evaluated by the error rate and converge speed of boosting classifier which is based on single feature. After that, the features are selected according to itpsilas classify power. The selected features are reassembled to B-feature vector. Then features are weighted according to its power in classification. The weighted B-feature vector is called B-W-Feature Vector. Three classifiers are used to evaluate the raw feature vector, the B-Feature and the B-W-Feature. The experiment results show selected and weighted feature vector can improve the classification performance.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"467 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114892550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
A Novel Method to Calculate Sample Weights for FCM Regression 一种计算FCM回归样本权值的新方法
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.122
Yan Zhu, Jian Yu
{"title":"A Novel Method to Calculate Sample Weights for FCM Regression","authors":"Yan Zhu, Jian Yu","doi":"10.1109/FSKD.2008.122","DOIUrl":"https://doi.org/10.1109/FSKD.2008.122","url":null,"abstract":"Regression is an important prediction method to establish models between variables. The primitive regression algorithms ignore the sample weights, and consider all samples play an equal role in regression. But this kind of algorithms often loses efficacy when dealing with outliers, since outliers disturb the regression models greatly. For traditional switching regression, sample membership varies with models when sample weights are equal. In this paper, we propose an adaptive sample weighting method for FCM regression, in which sample membership and sample weights are computed simultaneously. Such method can make outlier sample weights as small as possible. Numerical experiments suggest that our approach is effective.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114963386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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